Abstract
This study tries to examine the causal relationship between energy consumption and economic growth for twenty-nine provinces of China by employing the panel Granger causality analysis. The econometric methodology used in this paper allows us to untangle the causal nexus between energy consumption and economic growth and helps us to discriminate between competing theories on which hypothesis is applicable to China. Among the main results, it is found that there is no causality in two out of twenty-nine provinces and bidirectional causality is observed in sixteen out of twenty-nine provinces. Unidirectional causality is observed in eleven out of twenty-nine provinces of China. When bootstrap critical values are used, our empirical findings indicate that there is an unidirectional causal link running from real output to energy use for China, implying that economic growth significantly affects energy consumption, and hence, the conservation hypothesis is applicable to China.
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Notes
Variable x is said to Granger-cause variable y if y can be better predicted using the histories of both x and y than it can by using the history of y alone.
Bozoklu and Yilanci (2013) employ a Granger causality test in the frequency domain which allows them to distinguish short (temporary)- and long-run (permanent) causality.
Yalta and Cakar (2012) point out that “China is the most populous and the second largest economy in the world (International Monetary Fund 2010) with continuously increasing energy needs that cause a significant impact in energy prices and make the country a key player in the world energy markets. Moreover, China is the world’s largest emitter of greenhouse gases (GHGs), which leads to important environmental concerns, and also brings forth the question of whether sustainable growth can be achieved with energy conservation policies.”
To avoid the omitted variable bias, as shown in next section, we adopt the widely used production function approach which states that real output is a function of capital, labor and energy, all in natural logarithms.
Kónya (2006) suggests a different panel causality test which is based on the seemingly unrelated regressions (SUR) estimator proposed by Zellner (1962), and the Wald test with country-specific bootstrap critical values. Kónya’s (2006) test does not require pretesting for unit roots and cointegration apart from the lag structure. Nonetheless, this is an important problem since the unit root and the cointegration tests in general suffer from low power and different tests often lead to contradictory results. Nazlioglu et al. (2011), Chu (2012) and Chu and Chang (2012) apply Kónya’s (2006) approach to untangle the causal nexus between energy consumption and economic growth of the OECD and G-6 countries.
Note that the parameter restrictions (10) do not involve \(\delta \) and \(\phi \), so that the null hypothesis can be tested using a standard Wald statistic.
The 29 provinces are Beijing, Tianjin, Hebei, Shanxi, Inner Mongolia, Liaoning, Jilin, Heilongjiang, Shanghai, Jiangsu, Zhejiang, Anhui, Fujian, Jiangxi, Shandong, Henan, Hubei, Hunan, Guangdong, Guangxi, Hainan, Sichuan, Guizhou, Yunnan, Shaanxi, Gansu, Qinghai, Ningxia and Xinjiang.
Im et al. (2003) point that due to the heterogeneous nature of the alternative hypothesis in their test, caution has to be exercised when interpreting results because the null hypothesis of a unit root in each cross section may be rejected when only a fraction of the series in the panel is stationary. An additional concern here is that the presence of cross-sectional dependencies can undermine the asymptotic normality of the IPS test and lead to over-rejection of the null hypothesis of joint non-stationarity.
We code the panel Granger causality by using the Winrats software according to the MATLAB code provided by Professor Emirmahmutoglu. We thank him for providing us with his MATLAB code for reference.
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Acknowledgements
We would like to thank the editor, Professor Robert M. Kunst, and two anonymous referees of this journal for helpful comments and suggestions. The usual disclaimer applies. The second author is supported by the National Social Science Fund of China (No. 15ZDA054), National Natural Science Foundation of China (No. 71333007) and “The Fundamental Research Funds for the Central Universities.” The third author is supported by the National Natural Science Foundation of China (Nos. 71663026, 71273122, 41461025), Postdoctoral Science Foundation Grant of China (No. 2015M571981) and Jiangxi Social Science Fund (No. 15YJ11).
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Chen, SW., Xie, Z. & Liao, Y. Energy consumption promotes economic growth or economic growth causes energy use in China? A panel data analysis. Empir Econ 55, 1019–1043 (2018). https://doi.org/10.1007/s00181-017-1319-1
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DOI: https://doi.org/10.1007/s00181-017-1319-1